Enhancing fluidization stability and improving separation performance of fine lignite with vibrated gas‐solid fluidized bed
Bibliographic record
Abstract
A vibrated gas‐solid fluidized bed was proposed and tested to improve and upgrade fine lignite. A broad particle size (0.074–0.3 mm) of magnetite powder was prepared and used as main separating medium solids for coal improvement. The fluidization stability of the bed, including the fluidization index, fluctuations of bed pressure drop, and uniformity of bed density, was greatly enhanced by introducing the vibration energy to the static bed. The vibrated separation shows positive effects to improve the surface morphology of lignite and upgrade its quality to a certain degree. Ash‐content segregation of fine lignite samples obviously occurs by the joint effects of fluidized gas and vibration. The optimal segregation degree S ash values of 0.73 and 0.70 were achieved with suitable operating factors. The density‐dependent separation performance indicates that the ash and sulfur contents of lignite were sharply reduced with the probable error E values of 0.060 and 0.065 g/cm 3 . However, the overall E value for 6–1 mm sized fine lignite increases to 0.12 g/cm 3 due to the shift in the D 50 with particle size. The products of low‐ash clean coal, middlings, and high‐ash gangue were effectively obtained by successive separations. The dry coal improvement technology provides an alternative approach for the clean utilization of fine coal.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".